This time, as we did previously for a larger matrix, we will use the
routine in SPSS to run Pearson's correlation for water, sanitation, education and the
outcome variable waz score. Try this exercise:

3. Enter the list of variables (waz, dlowedn, notoilet,
dpiped, dwell) one-by-one into the variables box using the arrow key.

4. Click on the box to highlight Pearson's Correlation
Coefficient and the box for Two-tailed.

5. Click on OK.

INTERPRETATION:

Among the independent variables in the model, it is evident that there
is some collinearity. For example, the Low Education variable has a significant
correlation coefficient with toilet access (r = 0.169, p= .000) and piped water (r =
-0.152, p= 0.000). Toilet access has a significant correlation with both piped water (r =
-0.153, p=0.000) and well water (r = -0.158, p= 0.000). The collinearity which has been
detected here will need to be addressed when a model is developed to show the association
between water and sanitation with nutrition status. Return to the main text for some
ideas on how to confront this issue.